{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "b3db552f",
   "metadata": {},
   "source": [
    "# Mapping world countries to languages and Wikipedia language versions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "1336629e",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "317a3ea1",
   "metadata": {},
   "source": [
    "Import country-language list:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "e85158b2",
   "metadata": {},
   "outputs": [],
   "source": [
    "data = pd.read_csv(\"../data/raw/cldr/countries-languages.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "6654f971",
   "metadata": {},
   "outputs": [],
   "source": [
    "data.fillna(method='ffill', inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "b0bb39af",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Territory</th>\n",
       "      <th>Code</th>\n",
       "      <th>Terr. Literacy</th>\n",
       "      <th>Language</th>\n",
       "      <th>Code.1</th>\n",
       "      <th>Lang. Pop.</th>\n",
       "      <th>Pop.%</th>\n",
       "      <th>Literacy%</th>\n",
       "      <th>Written%</th>\n",
       "      <th>Report Bug</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>AF</td>\n",
       "      <td>28,00 %</td>\n",
       "      <td>Persian {O}</td>\n",
       "      <td>fa</td>\n",
       "      <td>18,000,000</td>\n",
       "      <td>50,00 %</td>\n",
       "      <td>28,00 %</td>\n",
       "      <td>28,00 %</td>\n",
       "      <td>bug</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>AF</td>\n",
       "      <td>28,00 %</td>\n",
       "      <td>Pashto {O}</td>\n",
       "      <td>ps</td>\n",
       "      <td>16,000,000</td>\n",
       "      <td>43,00 %</td>\n",
       "      <td>28,00 %</td>\n",
       "      <td>28,00 %</td>\n",
       "      <td>bug</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>AF</td>\n",
       "      <td>28,00 %</td>\n",
       "      <td>Hazaragi</td>\n",
       "      <td>haz</td>\n",
       "      <td>2,200,000</td>\n",
       "      <td>5.9%</td>\n",
       "      <td>28,00 %</td>\n",
       "      <td>28,00 %</td>\n",
       "      <td>bug</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>AF</td>\n",
       "      <td>28,00 %</td>\n",
       "      <td>Uzbek (Arabic) {OR}</td>\n",
       "      <td>uz_Arab</td>\n",
       "      <td>1,700,000</td>\n",
       "      <td>4.7%</td>\n",
       "      <td>28,00 %</td>\n",
       "      <td>28,00 %</td>\n",
       "      <td>bug</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>AF</td>\n",
       "      <td>28,00 %</td>\n",
       "      <td>Turkmen {OR}</td>\n",
       "      <td>tk</td>\n",
       "      <td>620</td>\n",
       "      <td>1.7%</td>\n",
       "      <td>28,00 %</td>\n",
       "      <td>28,00 %</td>\n",
       "      <td>bug</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1657</th>\n",
       "      <td>Zimbabwe</td>\n",
       "      <td>ZW</td>\n",
       "      <td>84,00 %</td>\n",
       "      <td>Kalanga</td>\n",
       "      <td>kck</td>\n",
       "      <td>770</td>\n",
       "      <td>5.3%</td>\n",
       "      <td>84,00 %</td>\n",
       "      <td>84,00 %</td>\n",
       "      <td>bug</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1658</th>\n",
       "      <td>Zimbabwe</td>\n",
       "      <td>ZW</td>\n",
       "      <td>84,00 %</td>\n",
       "      <td>Nyanja</td>\n",
       "      <td>ny</td>\n",
       "      <td>280</td>\n",
       "      <td>1.9%</td>\n",
       "      <td>84,00 %</td>\n",
       "      <td>84,00 %</td>\n",
       "      <td>bug</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1659</th>\n",
       "      <td>Zimbabwe</td>\n",
       "      <td>ZW</td>\n",
       "      <td>84,00 %</td>\n",
       "      <td>Venda</td>\n",
       "      <td>ve</td>\n",
       "      <td>93</td>\n",
       "      <td>0.64%</td>\n",
       "      <td>84,00 %</td>\n",
       "      <td>84,00 %</td>\n",
       "      <td>bug</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1660</th>\n",
       "      <td>Zimbabwe</td>\n",
       "      <td>ZW</td>\n",
       "      <td>84,00 %</td>\n",
       "      <td>Tswana</td>\n",
       "      <td>tn</td>\n",
       "      <td>32</td>\n",
       "      <td>0.22%</td>\n",
       "      <td>84,00 %</td>\n",
       "      <td>84,00 %</td>\n",
       "      <td>bug</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1661</th>\n",
       "      <td>Zimbabwe</td>\n",
       "      <td>ZW</td>\n",
       "      <td>84,00 %</td>\n",
       "      <td>add new</td>\n",
       "      <td></td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0%</td>\n",
       "      <td>0.0%</td>\n",
       "      <td>0.0%</td>\n",
       "      <td>bug</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1662 rows × 10 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        Territory Code Terr. Literacy             Language   Code.1  \\\n",
       "0     Afghanistan   AF        28,00 %          Persian {O}       fa   \n",
       "1     Afghanistan   AF        28,00 %           Pashto {O}       ps   \n",
       "2     Afghanistan   AF        28,00 %             Hazaragi      haz   \n",
       "3     Afghanistan   AF        28,00 %  Uzbek (Arabic) {OR}  uz_Arab   \n",
       "4     Afghanistan   AF        28,00 %         Turkmen {OR}       tk   \n",
       "...           ...  ...            ...                  ...      ...   \n",
       "1657     Zimbabwe   ZW        84,00 %              Kalanga      kck   \n",
       "1658     Zimbabwe   ZW        84,00 %               Nyanja       ny   \n",
       "1659     Zimbabwe   ZW        84,00 %                Venda       ve   \n",
       "1660     Zimbabwe   ZW        84,00 %               Tswana       tn   \n",
       "1661     Zimbabwe   ZW        84,00 %              add new            \n",
       "\n",
       "      Lang. Pop.    Pop.% Literacy% Written% Report Bug  \n",
       "0     18,000,000  50,00 %   28,00 %  28,00 %        bug  \n",
       "1     16,000,000  43,00 %   28,00 %  28,00 %        bug  \n",
       "2      2,200,000     5.9%   28,00 %  28,00 %        bug  \n",
       "3      1,700,000     4.7%   28,00 %  28,00 %        bug  \n",
       "4            620     1.7%   28,00 %  28,00 %        bug  \n",
       "...          ...      ...       ...      ...        ...  \n",
       "1657         770     5.3%   84,00 %  84,00 %        bug  \n",
       "1658         280     1.9%   84,00 %  84,00 %        bug  \n",
       "1659          93    0.64%   84,00 %  84,00 %        bug  \n",
       "1660          32    0.22%   84,00 %  84,00 %        bug  \n",
       "1661         0.0     0.0%      0.0%     0.0%        bug  \n",
       "\n",
       "[1662 rows x 10 columns]"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5fe0e071",
   "metadata": {},
   "source": [
    "Import list of wikipedias:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "0c9cd7fa",
   "metadata": {},
   "outputs": [],
   "source": [
    "with open(\"wikipedia-language-versions.txt\") as f:\n",
    "    wikis = f.readlines()\n",
    "wikis = [x.strip() for x in wikis]\n",
    "wikis[:] = [x for x in wikis if x]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "496d10a4",
   "metadata": {},
   "outputs": [],
   "source": [
    "wikis_top = ['en','ceb','de','sv','fr','nl','ru','es','it','arz','pl','ja','vi','war','zhe']"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7e886630",
   "metadata": {},
   "source": [
    "Create dictionaries for language code-country correspondence and country-language code correspondence:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "0c89bc57",
   "metadata": {},
   "outputs": [],
   "source": [
    "code_country_dict = {}\n",
    "country_code_dict = {}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "50f00c3b",
   "metadata": {},
   "outputs": [],
   "source": [
    "for index, row in data.iterrows():\n",
    "    if row['Code.1'] not in code_country_dict:\n",
    "        code_country_dict[row['Code.1']] = [row['Territory']]\n",
    "    else:\n",
    "        code_country_dict[row['Code.1']].append(row['Territory'])"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "14663f4f",
   "metadata": {},
   "source": [
    "Test for Polish:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "0041d705",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['Czechia', 'Germany', 'Israel', 'Poland', 'Romania', 'Slovakia', 'Ukraine']"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "code_country_dict['pl']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "b0bb3bc7",
   "metadata": {},
   "outputs": [],
   "source": [
    "for index, row in data.iterrows():\n",
    "    if row['Territory'] not in country_code_dict:\n",
    "        country_code_dict[row['Territory']] = [row['Code.1']]\n",
    "    else:\n",
    "        country_code_dict[row['Territory']].append(row['Code.1'])"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3e87666f",
   "metadata": {},
   "source": [
    "Test for Poland:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "bb5af2bf",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['ru',\n",
       " 'tt',\n",
       " 'ba',\n",
       " 'cv',\n",
       " 'hy',\n",
       " 'ce',\n",
       " 'av',\n",
       " 'udm',\n",
       " 'chm',\n",
       " 'os',\n",
       " 'sah',\n",
       " 'kbd',\n",
       " 'myv',\n",
       " 'dar',\n",
       " 'bua',\n",
       " 'mdf',\n",
       " 'kum',\n",
       " 'kv',\n",
       " 'lez',\n",
       " 'krc',\n",
       " 'inh',\n",
       " 'tyv',\n",
       " 'az_Cyrl',\n",
       " 'ady',\n",
       " 'krl',\n",
       " 'lbe',\n",
       " 'koi',\n",
       " 'mrj',\n",
       " 'alt',\n",
       " 'fi',\n",
       " 'sr_Latn',\n",
       " 'vep',\n",
       " 'mn',\n",
       " 'izh',\n",
       " 'cu',\n",
       " 'vot',\n",
       " ' ']"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "country_code_dict['Russia']"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "14340746",
   "metadata": {},
   "source": [
    "Import table with language versions and literary characters:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "9987cc7b",
   "metadata": {},
   "outputs": [],
   "source": [
    "pages = pd.read_csv(\"../data/raw/wikidata/figures.csv\")\n",
    "pages = pages.fillna(\"none\")\n",
    "pages.rename(columns={'article_en': 'en'}, inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "2efe3357",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>litFigLabel</th>\n",
       "      <th>litFig</th>\n",
       "      <th>en</th>\n",
       "      <th>aa</th>\n",
       "      <th>ab</th>\n",
       "      <th>ace</th>\n",
       "      <th>ady</th>\n",
       "      <th>af</th>\n",
       "      <th>ak</th>\n",
       "      <th>als</th>\n",
       "      <th>...</th>\n",
       "      <th>xmf</th>\n",
       "      <th>yi</th>\n",
       "      <th>yo</th>\n",
       "      <th>za</th>\n",
       "      <th>zea</th>\n",
       "      <th>zh-classical</th>\n",
       "      <th>zh-min-nan</th>\n",
       "      <th>zh-yue</th>\n",
       "      <th>zh</th>\n",
       "      <th>zu</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Pippi Longstocking</td>\n",
       "      <td>http://www.wikidata.org/entity/Q6668</td>\n",
       "      <td>https://en.wikipedia.org/wiki/Pippi_Longstocking</td>\n",
       "      <td>none</td>\n",
       "      <td>none</td>\n",
       "      <td>none</td>\n",
       "      <td>none</td>\n",
       "      <td>none</td>\n",
       "      <td>none</td>\n",
       "      <td>none</td>\n",
       "      <td>...</td>\n",
       "      <td>none</td>\n",
       "      <td>none</td>\n",
       "      <td>none</td>\n",
       "      <td>none</td>\n",
       "      <td>none</td>\n",
       "      <td>none</td>\n",
       "      <td>none</td>\n",
       "      <td>none</td>\n",
       "      <td>https://zh.wikipedia.org/wiki/%E9%95%BF%E8%A2%...</td>\n",
       "      <td>none</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Eragon</td>\n",
       "      <td>http://www.wikidata.org/entity/Q60702</td>\n",
       "      <td>https://en.wikipedia.org/wiki/Eragon_(character)</td>\n",
       "      <td>none</td>\n",
       "      <td>none</td>\n",
       "      <td>none</td>\n",
       "      <td>none</td>\n",
       "      <td>none</td>\n",
       "      <td>none</td>\n",
       "      <td>none</td>\n",
       "      <td>...</td>\n",
       "      <td>none</td>\n",
       "      <td>none</td>\n",
       "      <td>none</td>\n",
       "      <td>none</td>\n",
       "      <td>none</td>\n",
       "      <td>none</td>\n",
       "      <td>none</td>\n",
       "      <td>none</td>\n",
       "      <td>none</td>\n",
       "      <td>none</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Paige Matthews</td>\n",
       "      <td>http://www.wikidata.org/entity/Q60685</td>\n",
       "      <td>https://en.wikipedia.org/wiki/Paige_Matthews</td>\n",
       "      <td>none</td>\n",
       "      <td>none</td>\n",
       "      <td>none</td>\n",
       "      <td>none</td>\n",
       "      <td>none</td>\n",
       "      <td>none</td>\n",
       "      <td>none</td>\n",
       "      <td>...</td>\n",
       "      <td>none</td>\n",
       "      <td>none</td>\n",
       "      <td>none</td>\n",
       "      <td>none</td>\n",
       "      <td>none</td>\n",
       "      <td>none</td>\n",
       "      <td>none</td>\n",
       "      <td>none</td>\n",
       "      <td>none</td>\n",
       "      <td>none</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Katherine Pulaski</td>\n",
       "      <td>http://www.wikidata.org/entity/Q55191</td>\n",
       "      <td>https://en.wikipedia.org/wiki/Katherine_Pulaski</td>\n",
       "      <td>none</td>\n",
       "      <td>none</td>\n",
       "      <td>none</td>\n",
       "      <td>none</td>\n",
       "      <td>none</td>\n",
       "      <td>none</td>\n",
       "      <td>none</td>\n",
       "      <td>...</td>\n",
       "      <td>none</td>\n",
       "      <td>none</td>\n",
       "      <td>none</td>\n",
       "      <td>none</td>\n",
       "      <td>none</td>\n",
       "      <td>none</td>\n",
       "      <td>none</td>\n",
       "      <td>none</td>\n",
       "      <td>none</td>\n",
       "      <td>none</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Wedge Antilles</td>\n",
       "      <td>http://www.wikidata.org/entity/Q52310</td>\n",
       "      <td>https://en.wikipedia.org/wiki/Wedge_Antilles</td>\n",
       "      <td>none</td>\n",
       "      <td>none</td>\n",
       "      <td>none</td>\n",
       "      <td>none</td>\n",
       "      <td>none</td>\n",
       "      <td>none</td>\n",
       "      <td>none</td>\n",
       "      <td>...</td>\n",
       "      <td>none</td>\n",
       "      <td>none</td>\n",
       "      <td>none</td>\n",
       "      <td>none</td>\n",
       "      <td>none</td>\n",
       "      <td>none</td>\n",
       "      <td>none</td>\n",
       "      <td>none</td>\n",
       "      <td>none</td>\n",
       "      <td>none</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7038</th>\n",
       "      <td>Kapten</td>\n",
       "      <td>http://www.wikidata.org/entity/Q100155267</td>\n",
       "      <td>none</td>\n",
       "      <td>none</td>\n",
       "      <td>none</td>\n",
       "      <td>none</td>\n",
       "      <td>none</td>\n",
       "      <td>none</td>\n",
       "      <td>none</td>\n",
       "      <td>none</td>\n",
       "      <td>...</td>\n",
       "      <td>none</td>\n",
       "      <td>none</td>\n",
       "      <td>none</td>\n",
       "      <td>none</td>\n",
       "      <td>none</td>\n",
       "      <td>none</td>\n",
       "      <td>none</td>\n",
       "      <td>none</td>\n",
       "      <td>none</td>\n",
       "      <td>none</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7039</th>\n",
       "      <td>Beda</td>\n",
       "      <td>http://www.wikidata.org/entity/Q100155256</td>\n",
       "      <td>none</td>\n",
       "      <td>none</td>\n",
       "      <td>none</td>\n",
       "      <td>none</td>\n",
       "      <td>none</td>\n",
       "      <td>none</td>\n",
       "      <td>none</td>\n",
       "      <td>none</td>\n",
       "      <td>...</td>\n",
       "      <td>none</td>\n",
       "      <td>none</td>\n",
       "      <td>none</td>\n",
       "      <td>none</td>\n",
       "      <td>none</td>\n",
       "      <td>none</td>\n",
       "      <td>none</td>\n",
       "      <td>none</td>\n",
       "      <td>none</td>\n",
       "      <td>none</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7040</th>\n",
       "      <td>Olle Collin</td>\n",
       "      <td>http://www.wikidata.org/entity/Q100155242</td>\n",
       "      <td>none</td>\n",
       "      <td>none</td>\n",
       "      <td>none</td>\n",
       "      <td>none</td>\n",
       "      <td>none</td>\n",
       "      <td>none</td>\n",
       "      <td>none</td>\n",
       "      <td>none</td>\n",
       "      <td>...</td>\n",
       "      <td>none</td>\n",
       "      <td>none</td>\n",
       "      <td>none</td>\n",
       "      <td>none</td>\n",
       "      <td>none</td>\n",
       "      <td>none</td>\n",
       "      <td>none</td>\n",
       "      <td>none</td>\n",
       "      <td>none</td>\n",
       "      <td>none</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7041</th>\n",
       "      <td>Nolina Amundsen</td>\n",
       "      <td>http://www.wikidata.org/entity/Q100155230</td>\n",
       "      <td>none</td>\n",
       "      <td>none</td>\n",
       "      <td>none</td>\n",
       "      <td>none</td>\n",
       "      <td>none</td>\n",
       "      <td>none</td>\n",
       "      <td>none</td>\n",
       "      <td>none</td>\n",
       "      <td>...</td>\n",
       "      <td>none</td>\n",
       "      <td>none</td>\n",
       "      <td>none</td>\n",
       "      <td>none</td>\n",
       "      <td>none</td>\n",
       "      <td>none</td>\n",
       "      <td>none</td>\n",
       "      <td>none</td>\n",
       "      <td>none</td>\n",
       "      <td>none</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7042</th>\n",
       "      <td>Peter Pettigrew</td>\n",
       "      <td>http://www.wikidata.org/entity/Q1000118</td>\n",
       "      <td>https://en.wikipedia.org/wiki/Peter_Pettigrew_...</td>\n",
       "      <td>none</td>\n",
       "      <td>none</td>\n",
       "      <td>none</td>\n",
       "      <td>none</td>\n",
       "      <td>none</td>\n",
       "      <td>none</td>\n",
       "      <td>none</td>\n",
       "      <td>...</td>\n",
       "      <td>none</td>\n",
       "      <td>none</td>\n",
       "      <td>none</td>\n",
       "      <td>none</td>\n",
       "      <td>none</td>\n",
       "      <td>none</td>\n",
       "      <td>none</td>\n",
       "      <td>none</td>\n",
       "      <td>https://zh.wikipedia.org/wiki/%E5%BD%BC%E5%BE%...</td>\n",
       "      <td>none</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>7043 rows × 323 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "             litFigLabel                                     litFig  \\\n",
       "0     Pippi Longstocking       http://www.wikidata.org/entity/Q6668   \n",
       "1                 Eragon      http://www.wikidata.org/entity/Q60702   \n",
       "2         Paige Matthews      http://www.wikidata.org/entity/Q60685   \n",
       "3      Katherine Pulaski      http://www.wikidata.org/entity/Q55191   \n",
       "4         Wedge Antilles      http://www.wikidata.org/entity/Q52310   \n",
       "...                  ...                                        ...   \n",
       "7038              Kapten  http://www.wikidata.org/entity/Q100155267   \n",
       "7039                Beda  http://www.wikidata.org/entity/Q100155256   \n",
       "7040         Olle Collin  http://www.wikidata.org/entity/Q100155242   \n",
       "7041     Nolina Amundsen  http://www.wikidata.org/entity/Q100155230   \n",
       "7042     Peter Pettigrew    http://www.wikidata.org/entity/Q1000118   \n",
       "\n",
       "                                                     en    aa    ab   ace  \\\n",
       "0      https://en.wikipedia.org/wiki/Pippi_Longstocking  none  none  none   \n",
       "1      https://en.wikipedia.org/wiki/Eragon_(character)  none  none  none   \n",
       "2          https://en.wikipedia.org/wiki/Paige_Matthews  none  none  none   \n",
       "3       https://en.wikipedia.org/wiki/Katherine_Pulaski  none  none  none   \n",
       "4          https://en.wikipedia.org/wiki/Wedge_Antilles  none  none  none   \n",
       "...                                                 ...   ...   ...   ...   \n",
       "7038                                               none  none  none  none   \n",
       "7039                                               none  none  none  none   \n",
       "7040                                               none  none  none  none   \n",
       "7041                                               none  none  none  none   \n",
       "7042  https://en.wikipedia.org/wiki/Peter_Pettigrew_...  none  none  none   \n",
       "\n",
       "       ady    af    ak   als  ...   xmf    yi    yo    za   zea zh-classical  \\\n",
       "0     none  none  none  none  ...  none  none  none  none  none         none   \n",
       "1     none  none  none  none  ...  none  none  none  none  none         none   \n",
       "2     none  none  none  none  ...  none  none  none  none  none         none   \n",
       "3     none  none  none  none  ...  none  none  none  none  none         none   \n",
       "4     none  none  none  none  ...  none  none  none  none  none         none   \n",
       "...    ...   ...   ...   ...  ...   ...   ...   ...   ...   ...          ...   \n",
       "7038  none  none  none  none  ...  none  none  none  none  none         none   \n",
       "7039  none  none  none  none  ...  none  none  none  none  none         none   \n",
       "7040  none  none  none  none  ...  none  none  none  none  none         none   \n",
       "7041  none  none  none  none  ...  none  none  none  none  none         none   \n",
       "7042  none  none  none  none  ...  none  none  none  none  none         none   \n",
       "\n",
       "     zh-min-nan zh-yue                                                 zh  \\\n",
       "0          none   none  https://zh.wikipedia.org/wiki/%E9%95%BF%E8%A2%...   \n",
       "1          none   none                                               none   \n",
       "2          none   none                                               none   \n",
       "3          none   none                                               none   \n",
       "4          none   none                                               none   \n",
       "...         ...    ...                                                ...   \n",
       "7038       none   none                                               none   \n",
       "7039       none   none                                               none   \n",
       "7040       none   none                                               none   \n",
       "7041       none   none                                               none   \n",
       "7042       none   none  https://zh.wikipedia.org/wiki/%E5%BD%BC%E5%BE%...   \n",
       "\n",
       "        zu  \n",
       "0     none  \n",
       "1     none  \n",
       "2     none  \n",
       "3     none  \n",
       "4     none  \n",
       "...    ...  \n",
       "7038  none  \n",
       "7039  none  \n",
       "7040  none  \n",
       "7041  none  \n",
       "7042  none  \n",
       "\n",
       "[7043 rows x 323 columns]"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pages"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7edc6b40",
   "metadata": {},
   "source": [
    "Dictionary for language codes and number of character pages:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "993f0265",
   "metadata": {},
   "outputs": [],
   "source": [
    "code_figure_dict = {}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "8ac381fe",
   "metadata": {},
   "outputs": [],
   "source": [
    "for wiki in wikis:\n",
    "    number = 0\n",
    "    for line in pages[wiki]:\n",
    "        if line != 'none':\n",
    "            number = number + 1\n",
    "    code_figure_dict[wiki] = number"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "e079be0a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "474"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "code_figure_dict['de']"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "87b028f2",
   "metadata": {},
   "source": [
    "Dictionary for countries and number of character pages (= the sum of character pages for all languages spoken in that country:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "5d4206fe",
   "metadata": {},
   "outputs": [],
   "source": [
    "country_figures_dict = {}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "83d73243",
   "metadata": {},
   "outputs": [],
   "source": [
    "for country in country_code_dict:\n",
    "    number = 0\n",
    "    for code in country_code_dict[country]:\n",
    "        if code in wikis:\n",
    "            number = number + code_figure_dict[code]\n",
    "    country_figures_dict[country] = number"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cc90b424",
   "metadata": {},
   "source": [
    "End result:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "82aefc4d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'Afghanistan': 250,\n",
       " 'Åland Islands': 448,\n",
       " 'Albania': 195,\n",
       " 'Algeria': 3417,\n",
       " 'American Samoa': 1901,\n",
       " 'Andorra': 2574,\n",
       " 'Angola': 628,\n",
       " 'Anguilla': 1901,\n",
       " 'Antarctica': 0,\n",
       " 'Antigua & Barbuda': 2529,\n",
       " 'Argentina': 2918,\n",
       " 'Armenia': 244,\n",
       " 'Aruba': 2649,\n",
       " 'Ascension Island': 1901,\n",
       " 'Australia': 3362,\n",
       " 'Austria': 5632,\n",
       " 'Azerbaijan': 111,\n",
       " 'Bahamas': 1901,\n",
       " 'Bahrain': 306,\n",
       " 'Bangladesh': 1956,\n",
       " 'Barbados': 1901,\n",
       " 'Belarus': 817,\n",
       " 'Belgium': 4379,\n",
       " 'Belize': 2884,\n",
       " 'Benin': 1254,\n",
       " 'Bermuda': 1901,\n",
       " 'Bhutan': 1906,\n",
       " 'Bolivia': 984,\n",
       " 'Bosnia & Herzegovina': 2354,\n",
       " 'Botswana': 1924,\n",
       " 'Bouvet Island': 0,\n",
       " 'Brazil': 6528,\n",
       " 'British Indian Ocean Territory': 1901,\n",
       " 'British Virgin Islands': 1901,\n",
       " 'Brunei': 2045,\n",
       " 'Bulgaria': 3733,\n",
       " 'Burkina Faso': 1254,\n",
       " 'Burundi': 3160,\n",
       " 'Cambodia': 2,\n",
       " 'Cameroon': 3417,\n",
       " 'Canada': 5099,\n",
       " 'Canary Islands': 983,\n",
       " 'Cape Verde': 628,\n",
       " 'Caribbean Netherlands': 748,\n",
       " 'Cayman Islands': 1901,\n",
       " 'Central African Republic': 1254,\n",
       " 'Ceuta & Melilla': 983,\n",
       " 'Chad': 1516,\n",
       " 'Chile': 2884,\n",
       " 'China': 4307,\n",
       " 'Christmas Island': 1901,\n",
       " 'Clipperton Island': 0,\n",
       " 'Cocos (Keeling) Islands': 1901,\n",
       " 'Colombia': 983,\n",
       " 'Comoros': 1516,\n",
       " 'Congo - Brazzaville': 1254,\n",
       " 'Congo - Kinshasa': 1259,\n",
       " 'Cook Islands': 1901,\n",
       " 'Costa Rica': 983,\n",
       " 'Côte d’Ivoire': 1254,\n",
       " 'Croatia': 3552,\n",
       " 'Cuba': 983,\n",
       " 'Curaçao': 1731,\n",
       " 'Cyprus': 3998,\n",
       " 'Czechia': 3553,\n",
       " 'Denmark': 3049,\n",
       " 'Diego Garcia': 1901,\n",
       " 'Djibouti': 1516,\n",
       " 'Dominica': 1901,\n",
       " 'Dominican Republic': 2884,\n",
       " 'Ecuador': 984,\n",
       " 'Egypt': 2274,\n",
       " 'El Salvador': 983,\n",
       " 'Equatorial Guinea': 2865,\n",
       " 'Eritrea': 2164,\n",
       " 'Estonia': 3207,\n",
       " 'Eswatini': 1901,\n",
       " 'Ethiopia': 1908,\n",
       " 'Falkland Islands': 1901,\n",
       " 'Faroe Islands': 8,\n",
       " 'Fiji': 1936,\n",
       " 'Finland': 4133,\n",
       " 'France': 8074,\n",
       " 'French Guiana': 1254,\n",
       " 'French Polynesia': 1254,\n",
       " 'French Southern Territories': 1254,\n",
       " 'Gabon': 1254,\n",
       " 'Gambia': 1901,\n",
       " 'Georgia': 1027,\n",
       " 'Germany': 9248,\n",
       " 'Ghana': 1901,\n",
       " 'Gibraltar': 2884,\n",
       " 'Greece': 4415,\n",
       " 'Greenland': 218,\n",
       " 'Grenada': 1901,\n",
       " 'Guadeloupe': 1254,\n",
       " 'Guam': 1901,\n",
       " 'Guatemala': 983,\n",
       " 'Guernsey': 1901,\n",
       " 'Guinea': 1254,\n",
       " 'Guinea-Bissau': 628,\n",
       " 'Guyana': 1901,\n",
       " 'Haiti': 1254,\n",
       " 'Heard & McDonald Islands': 0,\n",
       " 'Honduras': 2884,\n",
       " 'Hong Kong SAR China': 2766,\n",
       " 'Hungary': 4468,\n",
       " 'Iceland': 259,\n",
       " 'India': 2206,\n",
       " 'Indonesia': 482,\n",
       " 'Iran': 771,\n",
       " 'Iraq': 2429,\n",
       " 'Ireland': 3177,\n",
       " 'Isle of Man': 1903,\n",
       " 'Israel': 4513,\n",
       " 'Italy': 5845,\n",
       " 'Jamaica': 1901,\n",
       " 'Japan': 1081,\n",
       " 'Jersey': 1901,\n",
       " 'Jordan': 2163,\n",
       " 'Kazakhstan': 3177,\n",
       " 'Kenya': 2202,\n",
       " 'Kiribati': 1901,\n",
       " 'Kosovo': 207,\n",
       " 'Kuwait': 262,\n",
       " 'Kyrgyzstan': 774,\n",
       " 'Laos': 1,\n",
       " 'Latvia': 2702,\n",
       " 'Lebanon': 3550,\n",
       " 'Lesotho': 1901,\n",
       " 'Liberia': 1901,\n",
       " 'Libya': 262,\n",
       " 'Liechtenstein': 474,\n",
       " 'Lithuania': 3198,\n",
       " 'Luxembourg': 4276,\n",
       " 'Macao SAR China': 3394,\n",
       " 'Madagascar': 3163,\n",
       " 'Malawi': 1901,\n",
       " 'Malaysia': 3008,\n",
       " 'Maldives': 0,\n",
       " 'Mali': 1516,\n",
       " 'Malta': 4617,\n",
       " 'Marshall Islands': 1901,\n",
       " 'Martinique': 1254,\n",
       " 'Mauritania': 1516,\n",
       " 'Mauritius': 3206,\n",
       " 'Mayotte': 1259,\n",
       " 'Mexico': 2884,\n",
       " 'Micronesia': 1901,\n",
       " 'Moldova': 1611,\n",
       " 'Monaco': 1254,\n",
       " 'Mongolia': 1643,\n",
       " 'Montenegro': 207,\n",
       " 'Montserrat': 1901,\n",
       " 'Morocco': 4402,\n",
       " 'Mozambique': 633,\n",
       " 'Myanmar (Burma)': 11,\n",
       " 'Namibia': 2398,\n",
       " 'Nauru': 1901,\n",
       " 'Nepal': 2007,\n",
       " 'Netherlands': 5068,\n",
       " 'New Caledonia': 1254,\n",
       " 'New Zealand': 1901,\n",
       " 'Nicaragua': 983,\n",
       " 'Niger': 1516,\n",
       " 'Nigeria': 2163,\n",
       " 'Niue': 1901,\n",
       " 'Norfolk Island': 1901,\n",
       " 'North Korea': 325,\n",
       " 'North Macedonia': 457,\n",
       " 'Northern Mariana Islands': 1901,\n",
       " 'Norway': 69,\n",
       " 'Oman': 509,\n",
       " 'Pakistan': 2176,\n",
       " 'Palau': 1901,\n",
       " 'Palestinian Territories': 262,\n",
       " 'Panama': 2884,\n",
       " 'Papua New Guinea': 1901,\n",
       " 'Paraguay': 1457,\n",
       " 'Peru': 984,\n",
       " 'Philippines': 2901,\n",
       " 'Pitcairn Islands': 1901,\n",
       " 'Poland': 4396,\n",
       " 'Portugal': 4852,\n",
       " 'Puerto Rico': 2884,\n",
       " 'Qatar': 553,\n",
       " 'Réunion': 1284,\n",
       " 'Romania': 6542,\n",
       " 'Russia': 1335,\n",
       " 'Rwanda': 3155,\n",
       " 'Samoa': 1901,\n",
       " 'San Marino': 1575,\n",
       " 'São Tomé & Príncipe': 628,\n",
       " 'Saudi Arabia': 262,\n",
       " 'Senegal': 1254,\n",
       " 'Serbia': 1313,\n",
       " 'Seychelles': 3155,\n",
       " 'Sierra Leone': 1901,\n",
       " 'Singapore': 3005,\n",
       " 'Sint Maarten': 3631,\n",
       " 'Slovakia': 4165,\n",
       " 'Slovenia': 4371,\n",
       " 'Solomon Islands': 1901,\n",
       " 'Somalia': 267,\n",
       " 'South Africa': 1964,\n",
       " 'South Georgia & South Sandwich Islands': 0,\n",
       " 'South Korea': 325,\n",
       " 'South Sudan': 2163,\n",
       " 'Spain': 3481,\n",
       " 'Sri Lanka': 1944,\n",
       " 'St. Barthélemy': 1254,\n",
       " 'St. Helena': 1901,\n",
       " 'St. Kitts & Nevis': 1901,\n",
       " 'St. Lucia': 1901,\n",
       " 'St. Martin': 1254,\n",
       " 'St. Pierre & Miquelon': 3155,\n",
       " 'St. Vincent & Grenadines': 1901,\n",
       " 'Sudan': 2163,\n",
       " 'Suriname': 747,\n",
       " 'Svalbard & Jan Mayen': 767,\n",
       " 'Sweden': 2816,\n",
       " 'Switzerland': 5722,\n",
       " 'Syria': 1664,\n",
       " 'Taiwan': 0,\n",
       " 'Tajikistan': 1279,\n",
       " 'Tanzania': 1906,\n",
       " 'Thailand': 2109,\n",
       " 'Timor-Leste': 628,\n",
       " 'Togo': 1254,\n",
       " 'Tokelau': 1901,\n",
       " 'Tonga': 1901,\n",
       " 'Trinidad & Tobago': 2884,\n",
       " 'Tristan da Cunha': 1901,\n",
       " 'Tunisia': 1516,\n",
       " 'Turkey': 3315,\n",
       " 'Turkmenistan': 808,\n",
       " 'Turks & Caicos Islands': 1901,\n",
       " 'Tuvalu': 1901,\n",
       " 'U.S. Outlying Islands': 1901,\n",
       " 'U.S. Virgin Islands': 1901,\n",
       " 'Uganda': 1941,\n",
       " 'Ukraine': 3129,\n",
       " 'United Arab Emirates': 2456,\n",
       " 'United Kingdom': 5372,\n",
       " 'United States': 7494,\n",
       " 'Uruguay': 983,\n",
       " 'Uzbekistan': 1148,\n",
       " 'Vanuatu': 3155,\n",
       " 'Vatican City': 1567,\n",
       " 'Venezuela': 983,\n",
       " 'Vietnam': 317,\n",
       " 'Wallis & Futuna': 1254,\n",
       " 'Western Sahara': 262,\n",
       " 'Yemen': 2163,\n",
       " 'Zambia': 1901,\n",
       " 'Zimbabwe': 1902}"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "country_figures_dict"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "26377ed5",
   "metadata": {},
   "source": [
    "(Alternative version: only count the wikis, not their number of articles:)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "id": "e2f1d45f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'Afghanistan': 0,\n",
       " 'Åland Islands': 1,\n",
       " 'Albania': 0,\n",
       " 'Algeria': 2,\n",
       " 'American Samoa': 1,\n",
       " 'Andorra': 2,\n",
       " 'Angola': 0,\n",
       " 'Anguilla': 1,\n",
       " 'Antarctica': 0,\n",
       " 'Antigua & Barbuda': 1,\n",
       " 'Argentina': 2,\n",
       " 'Armenia': 0,\n",
       " 'Aruba': 2,\n",
       " 'Ascension Island': 1,\n",
       " 'Australia': 2,\n",
       " 'Austria': 4,\n",
       " 'Azerbaijan': 0,\n",
       " 'Bahamas': 1,\n",
       " 'Bahrain': 0,\n",
       " 'Bangladesh': 1,\n",
       " 'Barbados': 1,\n",
       " 'Belarus': 1,\n",
       " 'Belgium': 4,\n",
       " 'Belize': 2,\n",
       " 'Benin': 1,\n",
       " 'Bermuda': 1,\n",
       " 'Bhutan': 1,\n",
       " 'Bolivia': 1,\n",
       " 'Bosnia & Herzegovina': 1,\n",
       " 'Botswana': 1,\n",
       " 'Bouvet Island': 0,\n",
       " 'Brazil': 5,\n",
       " 'British Indian Ocean Territory': 1,\n",
       " 'British Virgin Islands': 1,\n",
       " 'Brunei': 1,\n",
       " 'Bulgaria': 3,\n",
       " 'Burkina Faso': 1,\n",
       " 'Burundi': 2,\n",
       " 'Cambodia': 0,\n",
       " 'Cameroon': 2,\n",
       " 'Canada': 4,\n",
       " 'Canary Islands': 1,\n",
       " 'Cape Verde': 0,\n",
       " 'Caribbean Netherlands': 1,\n",
       " 'Cayman Islands': 1,\n",
       " 'Central African Republic': 1,\n",
       " 'Ceuta & Melilla': 1,\n",
       " 'Chad': 1,\n",
       " 'Chile': 2,\n",
       " 'China': 3,\n",
       " 'Christmas Island': 1,\n",
       " 'Clipperton Island': 0,\n",
       " 'Cocos (Keeling) Islands': 1,\n",
       " 'Colombia': 1,\n",
       " 'Comoros': 1,\n",
       " 'Congo - Brazzaville': 1,\n",
       " 'Congo - Kinshasa': 1,\n",
       " 'Cook Islands': 1,\n",
       " 'Costa Rica': 1,\n",
       " 'Côte d’Ivoire': 1,\n",
       " 'Croatia': 2,\n",
       " 'Cuba': 1,\n",
       " 'Curaçao': 2,\n",
       " 'Cyprus': 2,\n",
       " 'Czechia': 3,\n",
       " 'Denmark': 3,\n",
       " 'Diego Garcia': 1,\n",
       " 'Djibouti': 1,\n",
       " 'Dominica': 1,\n",
       " 'Dominican Republic': 2,\n",
       " 'Ecuador': 1,\n",
       " 'Egypt': 2,\n",
       " 'El Salvador': 1,\n",
       " 'Equatorial Guinea': 2,\n",
       " 'Eritrea': 1,\n",
       " 'Estonia': 2,\n",
       " 'Eswatini': 1,\n",
       " 'Ethiopia': 1,\n",
       " 'Falkland Islands': 1,\n",
       " 'Faroe Islands': 0,\n",
       " 'Fiji': 1,\n",
       " 'Finland': 4,\n",
       " 'France': 6,\n",
       " 'French Guiana': 1,\n",
       " 'French Polynesia': 1,\n",
       " 'French Southern Territories': 1,\n",
       " 'Gabon': 1,\n",
       " 'Gambia': 1,\n",
       " 'Georgia': 1,\n",
       " 'Germany': 8,\n",
       " 'Ghana': 1,\n",
       " 'Gibraltar': 2,\n",
       " 'Greece': 3,\n",
       " 'Greenland': 0,\n",
       " 'Grenada': 1,\n",
       " 'Guadeloupe': 1,\n",
       " 'Guam': 1,\n",
       " 'Guatemala': 1,\n",
       " 'Guernsey': 1,\n",
       " 'Guinea': 1,\n",
       " 'Guinea-Bissau': 0,\n",
       " 'Guyana': 1,\n",
       " 'Haiti': 1,\n",
       " 'Heard & McDonald Islands': 0,\n",
       " 'Honduras': 2,\n",
       " 'Hong Kong SAR China': 1,\n",
       " 'Hungary': 3,\n",
       " 'Iceland': 0,\n",
       " 'India': 1,\n",
       " 'Indonesia': 0,\n",
       " 'Iran': 0,\n",
       " 'Iraq': 1,\n",
       " 'Ireland': 2,\n",
       " 'Isle of Man': 1,\n",
       " 'Israel': 3,\n",
       " 'Italy': 4,\n",
       " 'Jamaica': 1,\n",
       " 'Japan': 1,\n",
       " 'Jersey': 1,\n",
       " 'Jordan': 1,\n",
       " 'Kazakhstan': 3,\n",
       " 'Kenya': 1,\n",
       " 'Kiribati': 1,\n",
       " 'Kosovo': 0,\n",
       " 'Kuwait': 0,\n",
       " 'Kyrgyzstan': 1,\n",
       " 'Laos': 0,\n",
       " 'Latvia': 2,\n",
       " 'Lebanon': 2,\n",
       " 'Lesotho': 1,\n",
       " 'Liberia': 1,\n",
       " 'Libya': 0,\n",
       " 'Liechtenstein': 1,\n",
       " 'Lithuania': 3,\n",
       " 'Luxembourg': 3,\n",
       " 'Macao SAR China': 1,\n",
       " 'Madagascar': 2,\n",
       " 'Malawi': 1,\n",
       " 'Malaysia': 1,\n",
       " 'Maldives': 0,\n",
       " 'Mali': 1,\n",
       " 'Malta': 3,\n",
       " 'Marshall Islands': 1,\n",
       " 'Martinique': 1,\n",
       " 'Mauritania': 1,\n",
       " 'Mauritius': 2,\n",
       " 'Mayotte': 1,\n",
       " 'Mexico': 2,\n",
       " 'Micronesia': 1,\n",
       " 'Moldova': 1,\n",
       " 'Monaco': 1,\n",
       " 'Mongolia': 1,\n",
       " 'Montenegro': 0,\n",
       " 'Montserrat': 1,\n",
       " 'Morocco': 3,\n",
       " 'Mozambique': 0,\n",
       " 'Myanmar (Burma)': 0,\n",
       " 'Namibia': 2,\n",
       " 'Nauru': 1,\n",
       " 'Nepal': 1,\n",
       " 'Netherlands': 4,\n",
       " 'New Caledonia': 1,\n",
       " 'New Zealand': 1,\n",
       " 'Nicaragua': 1,\n",
       " 'Niger': 1,\n",
       " 'Nigeria': 1,\n",
       " 'Niue': 1,\n",
       " 'Norfolk Island': 1,\n",
       " 'North Korea': 0,\n",
       " 'North Macedonia': 0,\n",
       " 'Northern Mariana Islands': 1,\n",
       " 'Norway': 0,\n",
       " 'Oman': 0,\n",
       " 'Pakistan': 1,\n",
       " 'Palau': 1,\n",
       " 'Palestinian Territories': 0,\n",
       " 'Panama': 2,\n",
       " 'Papua New Guinea': 1,\n",
       " 'Paraguay': 2,\n",
       " 'Peru': 1,\n",
       " 'Philippines': 4,\n",
       " 'Pitcairn Islands': 1,\n",
       " 'Poland': 4,\n",
       " 'Portugal': 3,\n",
       " 'Puerto Rico': 2,\n",
       " 'Qatar': 0,\n",
       " 'Réunion': 1,\n",
       " 'Romania': 5,\n",
       " 'Russia': 1,\n",
       " 'Rwanda': 2,\n",
       " 'Samoa': 1,\n",
       " 'San Marino': 1,\n",
       " 'São Tomé & Príncipe': 0,\n",
       " 'Saudi Arabia': 0,\n",
       " 'Senegal': 1,\n",
       " 'Serbia': 0,\n",
       " 'Seychelles': 2,\n",
       " 'Sierra Leone': 1,\n",
       " 'Singapore': 1,\n",
       " 'Sint Maarten': 3,\n",
       " 'Slovakia': 3,\n",
       " 'Slovenia': 3,\n",
       " 'Solomon Islands': 1,\n",
       " 'Somalia': 0,\n",
       " 'South Africa': 1,\n",
       " 'South Georgia & South Sandwich Islands': 0,\n",
       " 'South Korea': 0,\n",
       " 'South Sudan': 1,\n",
       " 'Spain': 2,\n",
       " 'Sri Lanka': 1,\n",
       " 'St. Barthélemy': 1,\n",
       " 'St. Helena': 1,\n",
       " 'St. Kitts & Nevis': 1,\n",
       " 'St. Lucia': 1,\n",
       " 'St. Martin': 1,\n",
       " 'St. Pierre & Miquelon': 2,\n",
       " 'St. Vincent & Grenadines': 1,\n",
       " 'Sudan': 1,\n",
       " 'Suriname': 1,\n",
       " 'Svalbard & Jan Mayen': 1,\n",
       " 'Sweden': 2,\n",
       " 'Switzerland': 4,\n",
       " 'Syria': 1,\n",
       " 'Taiwan': 0,\n",
       " 'Tajikistan': 1,\n",
       " 'Tanzania': 1,\n",
       " 'Thailand': 1,\n",
       " 'Timor-Leste': 0,\n",
       " 'Togo': 1,\n",
       " 'Tokelau': 1,\n",
       " 'Tonga': 1,\n",
       " 'Trinidad & Tobago': 2,\n",
       " 'Tristan da Cunha': 1,\n",
       " 'Tunisia': 1,\n",
       " 'Turkey': 1,\n",
       " 'Turkmenistan': 1,\n",
       " 'Turks & Caicos Islands': 1,\n",
       " 'Tuvalu': 1,\n",
       " 'U.S. Outlying Islands': 1,\n",
       " 'U.S. Virgin Islands': 1,\n",
       " 'Uganda': 1,\n",
       " 'Ukraine': 2,\n",
       " 'United Arab Emirates': 1,\n",
       " 'United Kingdom': 4,\n",
       " 'United States': 7,\n",
       " 'Uruguay': 1,\n",
       " 'Uzbekistan': 1,\n",
       " 'Vanuatu': 2,\n",
       " 'Vatican City': 1,\n",
       " 'Venezuela': 1,\n",
       " 'Vietnam': 1,\n",
       " 'Wallis & Futuna': 1,\n",
       " 'Western Sahara': 0,\n",
       " 'Yemen': 1,\n",
       " 'Zambia': 1,\n",
       " 'Zimbabwe': 1}"
      ]
     },
     "execution_count": 71,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "country_figures_dict = {}\n",
    "for country in country_code_dict:\n",
    "    number = 0\n",
    "    for code in country_code_dict[country]:\n",
    "        if code in wikis_top:\n",
    "            if code_figure_dict[code] > 0:\n",
    "                number = number + 1\n",
    "    country_figures_dict[country] = number\n",
    "country_figures_dict"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "id": "87eb7ea2",
   "metadata": {},
   "outputs": [],
   "source": [
    "country_figures_dict['United States of America'] = country_figures_dict['United States']\n",
    "del country_figures_dict['United States']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "id": "9951dbb1",
   "metadata": {},
   "outputs": [],
   "source": [
    "country_figures_dict['Trinidad and Tobago'] = country_figures_dict['Trinidad & Tobago']\n",
    "del country_figures_dict['Trinidad & Tobago']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "id": "04f52bd2",
   "metadata": {},
   "outputs": [],
   "source": [
    "country_figures_dict['S. Sudan'] = country_figures_dict['South Sudan']\n",
    "del country_figures_dict['South Sudan']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "id": "e64efb10",
   "metadata": {},
   "outputs": [],
   "source": [
    "country_figures_dict['W. Sahara'] = country_figures_dict['Western Sahara']\n",
    "del country_figures_dict['Western Sahara']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "id": "0ef1df95",
   "metadata": {},
   "outputs": [],
   "source": [
    "country_figures_dict['Dem. Rep. Congo'] = country_figures_dict['Congo - Kinshasa']\n",
    "del country_figures_dict['Congo - Kinshasa']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "id": "fdf2f465",
   "metadata": {},
   "outputs": [],
   "source": [
    "country_figures_dict['Congo'] = country_figures_dict['Congo - Brazzaville']\n",
    "del country_figures_dict['Congo - Brazzaville']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "id": "9384d352",
   "metadata": {},
   "outputs": [],
   "source": [
    "country_figures_dict['Dominican Rep.'] = country_figures_dict['Dominican Republic']\n",
    "del country_figures_dict['Dominican Republic']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "id": "31c56236",
   "metadata": {},
   "outputs": [],
   "source": [
    "country_figures_dict['Falkland Is.'] = country_figures_dict['Falkland Islands']\n",
    "del country_figures_dict['Falkland Islands']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 80,
   "id": "e12293f1",
   "metadata": {},
   "outputs": [],
   "source": [
    "country_figures_dict['Central African Rep.'] = country_figures_dict['Central African Republic']\n",
    "del country_figures_dict['Central African Republic']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 81,
   "id": "bf156630",
   "metadata": {},
   "outputs": [],
   "source": [
    "country_figures_dict['Eq. Guinea'] = country_figures_dict['Equatorial Guinea']\n",
    "del country_figures_dict['Equatorial Guinea']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "id": "5656620e",
   "metadata": {},
   "outputs": [],
   "source": [
    "country_figures_dict['eSwatini'] = country_figures_dict['Eswatini']\n",
    "del country_figures_dict['Eswatini']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 83,
   "id": "3021566f",
   "metadata": {},
   "outputs": [],
   "source": [
    "country_figures_dict['Palestine'] = country_figures_dict['Palestinian Territories']\n",
    "del country_figures_dict['Palestinian Territories']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 84,
   "id": "e98e0933",
   "metadata": {},
   "outputs": [],
   "source": [
    "country_figures_dict['Myanmar'] = country_figures_dict['Myanmar (Burma)']\n",
    "del country_figures_dict['Myanmar (Burma)']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 85,
   "id": "4f6232cc",
   "metadata": {},
   "outputs": [],
   "source": [
    "country_figures_dict['Solomon Is.'] = country_figures_dict['Solomon Islands']\n",
    "del country_figures_dict['Solomon Islands']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 86,
   "id": "826049f1",
   "metadata": {},
   "outputs": [],
   "source": [
    "country_figures_dict['Bosnia and Herz.'] = country_figures_dict['Bosnia & Herzegovina']\n",
    "del country_figures_dict['Bosnia & Herzegovina']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 87,
   "id": "298f59f4",
   "metadata": {},
   "outputs": [],
   "source": [
    "country_figures_dict['Macedonia'] = country_figures_dict['North Macedonia']\n",
    "del country_figures_dict['North Macedonia']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 88,
   "id": "aedf4086",
   "metadata": {},
   "outputs": [],
   "source": [
    "country_figures_dict['Fr. S. Antarctic Lands'] = country_figures_dict['French Southern Territories']\n",
    "del country_figures_dict['French Southern Territories']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 89,
   "id": "b62458dd",
   "metadata": {},
   "outputs": [],
   "source": [
    "country_figures_dict['''Côte d'Ivoire'''] = country_figures_dict['Côte d’Ivoire']\n",
    "del country_figures_dict['Côte d’Ivoire']"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6cbf5e03",
   "metadata": {},
   "source": [
    "# Plotting the world map\n",
    "\n",
    "Great tutorial [here](https://medium.com/@barua.aindriya/visualize-data-on-a-choropleth-map-with-geopandas-and-matplotlib-924cedd8e9cb)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 90,
   "id": "0f422959",
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "import geopandas as gpd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 91,
   "id": "d54f5c1b",
   "metadata": {},
   "outputs": [],
   "source": [
    "country_character_df = pd.DataFrame(list(country_figures_dict.items()), columns=['country', 'characters'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 92,
   "id": "0cf903a1",
   "metadata": {},
   "outputs": [],
   "source": [
    "world = gpd.read_file(gpd.datasets.get_path('naturalearth_lowres'))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 93,
   "id": "3edef9c4",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>pop_est</th>\n",
       "      <th>continent</th>\n",
       "      <th>name</th>\n",
       "      <th>iso_a3</th>\n",
       "      <th>gdp_md_est</th>\n",
       "      <th>geometry</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>920938</td>\n",
       "      <td>Oceania</td>\n",
       "      <td>Fiji</td>\n",
       "      <td>FJI</td>\n",
       "      <td>8374.0</td>\n",
       "      <td>MULTIPOLYGON (((180.00000 -16.06713, 180.00000...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>53950935</td>\n",
       "      <td>Africa</td>\n",
       "      <td>Tanzania</td>\n",
       "      <td>TZA</td>\n",
       "      <td>150600.0</td>\n",
       "      <td>POLYGON ((33.90371 -0.95000, 34.07262 -1.05982...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>603253</td>\n",
       "      <td>Africa</td>\n",
       "      <td>W. Sahara</td>\n",
       "      <td>ESH</td>\n",
       "      <td>906.5</td>\n",
       "      <td>POLYGON ((-8.66559 27.65643, -8.66512 27.58948...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>35623680</td>\n",
       "      <td>North America</td>\n",
       "      <td>Canada</td>\n",
       "      <td>CAN</td>\n",
       "      <td>1674000.0</td>\n",
       "      <td>MULTIPOLYGON (((-122.84000 49.00000, -122.9742...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>326625791</td>\n",
       "      <td>North America</td>\n",
       "      <td>United States of America</td>\n",
       "      <td>USA</td>\n",
       "      <td>18560000.0</td>\n",
       "      <td>MULTIPOLYGON (((-122.84000 49.00000, -120.0000...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>172</th>\n",
       "      <td>7111024</td>\n",
       "      <td>Europe</td>\n",
       "      <td>Serbia</td>\n",
       "      <td>SRB</td>\n",
       "      <td>101800.0</td>\n",
       "      <td>POLYGON ((18.82982 45.90887, 18.82984 45.90888...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>173</th>\n",
       "      <td>642550</td>\n",
       "      <td>Europe</td>\n",
       "      <td>Montenegro</td>\n",
       "      <td>MNE</td>\n",
       "      <td>10610.0</td>\n",
       "      <td>POLYGON ((20.07070 42.58863, 19.80161 42.50009...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>174</th>\n",
       "      <td>1895250</td>\n",
       "      <td>Europe</td>\n",
       "      <td>Kosovo</td>\n",
       "      <td>-99</td>\n",
       "      <td>18490.0</td>\n",
       "      <td>POLYGON ((20.59025 41.85541, 20.52295 42.21787...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>175</th>\n",
       "      <td>1218208</td>\n",
       "      <td>North America</td>\n",
       "      <td>Trinidad and Tobago</td>\n",
       "      <td>TTO</td>\n",
       "      <td>43570.0</td>\n",
       "      <td>POLYGON ((-61.68000 10.76000, -61.10500 10.890...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>176</th>\n",
       "      <td>13026129</td>\n",
       "      <td>Africa</td>\n",
       "      <td>S. Sudan</td>\n",
       "      <td>SSD</td>\n",
       "      <td>20880.0</td>\n",
       "      <td>POLYGON ((30.83385 3.50917, 29.95350 4.17370, ...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>177 rows × 6 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       pop_est      continent                      name iso_a3  gdp_md_est  \\\n",
       "0       920938        Oceania                      Fiji    FJI      8374.0   \n",
       "1     53950935         Africa                  Tanzania    TZA    150600.0   \n",
       "2       603253         Africa                 W. Sahara    ESH       906.5   \n",
       "3     35623680  North America                    Canada    CAN   1674000.0   \n",
       "4    326625791  North America  United States of America    USA  18560000.0   \n",
       "..         ...            ...                       ...    ...         ...   \n",
       "172    7111024         Europe                    Serbia    SRB    101800.0   \n",
       "173     642550         Europe                Montenegro    MNE     10610.0   \n",
       "174    1895250         Europe                    Kosovo    -99     18490.0   \n",
       "175    1218208  North America       Trinidad and Tobago    TTO     43570.0   \n",
       "176   13026129         Africa                  S. Sudan    SSD     20880.0   \n",
       "\n",
       "                                              geometry  \n",
       "0    MULTIPOLYGON (((180.00000 -16.06713, 180.00000...  \n",
       "1    POLYGON ((33.90371 -0.95000, 34.07262 -1.05982...  \n",
       "2    POLYGON ((-8.66559 27.65643, -8.66512 27.58948...  \n",
       "3    MULTIPOLYGON (((-122.84000 49.00000, -122.9742...  \n",
       "4    MULTIPOLYGON (((-122.84000 49.00000, -120.0000...  \n",
       "..                                                 ...  \n",
       "172  POLYGON ((18.82982 45.90887, 18.82984 45.90888...  \n",
       "173  POLYGON ((20.07070 42.58863, 19.80161 42.50009...  \n",
       "174  POLYGON ((20.59025 41.85541, 20.52295 42.21787...  \n",
       "175  POLYGON ((-61.68000 10.76000, -61.10500 10.890...  \n",
       "176  POLYGON ((30.83385 3.50917, 29.95350 4.17370, ...  \n",
       "\n",
       "[177 rows x 6 columns]"
      ]
     },
     "execution_count": 93,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "world"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 94,
   "id": "aeaffef0",
   "metadata": {},
   "outputs": [],
   "source": [
    "merged = world.set_index('name').join(country_character_df.set_index('country'))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 95,
   "id": "c8923281",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>pop_est</th>\n",
       "      <th>continent</th>\n",
       "      <th>iso_a3</th>\n",
       "      <th>gdp_md_est</th>\n",
       "      <th>geometry</th>\n",
       "      <th>characters</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>name</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Fiji</th>\n",
       "      <td>920938</td>\n",
       "      <td>Oceania</td>\n",
       "      <td>FJI</td>\n",
       "      <td>8374.0</td>\n",
       "      <td>MULTIPOLYGON (((180.00000 -16.06713, 180.00000...</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Tanzania</th>\n",
       "      <td>53950935</td>\n",
       "      <td>Africa</td>\n",
       "      <td>TZA</td>\n",
       "      <td>150600.0</td>\n",
       "      <td>POLYGON ((33.90371 -0.95000, 34.07262 -1.05982...</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>W. Sahara</th>\n",
       "      <td>603253</td>\n",
       "      <td>Africa</td>\n",
       "      <td>ESH</td>\n",
       "      <td>906.5</td>\n",
       "      <td>POLYGON ((-8.66559 27.65643, -8.66512 27.58948...</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Canada</th>\n",
       "      <td>35623680</td>\n",
       "      <td>North America</td>\n",
       "      <td>CAN</td>\n",
       "      <td>1674000.0</td>\n",
       "      <td>MULTIPOLYGON (((-122.84000 49.00000, -122.9742...</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>United States of America</th>\n",
       "      <td>326625791</td>\n",
       "      <td>North America</td>\n",
       "      <td>USA</td>\n",
       "      <td>18560000.0</td>\n",
       "      <td>MULTIPOLYGON (((-122.84000 49.00000, -120.0000...</td>\n",
       "      <td>7.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Serbia</th>\n",
       "      <td>7111024</td>\n",
       "      <td>Europe</td>\n",
       "      <td>SRB</td>\n",
       "      <td>101800.0</td>\n",
       "      <td>POLYGON ((18.82982 45.90887, 18.82984 45.90888...</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Montenegro</th>\n",
       "      <td>642550</td>\n",
       "      <td>Europe</td>\n",
       "      <td>MNE</td>\n",
       "      <td>10610.0</td>\n",
       "      <td>POLYGON ((20.07070 42.58863, 19.80161 42.50009...</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Kosovo</th>\n",
       "      <td>1895250</td>\n",
       "      <td>Europe</td>\n",
       "      <td>-99</td>\n",
       "      <td>18490.0</td>\n",
       "      <td>POLYGON ((20.59025 41.85541, 20.52295 42.21787...</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Trinidad and Tobago</th>\n",
       "      <td>1218208</td>\n",
       "      <td>North America</td>\n",
       "      <td>TTO</td>\n",
       "      <td>43570.0</td>\n",
       "      <td>POLYGON ((-61.68000 10.76000, -61.10500 10.890...</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>S. Sudan</th>\n",
       "      <td>13026129</td>\n",
       "      <td>Africa</td>\n",
       "      <td>SSD</td>\n",
       "      <td>20880.0</td>\n",
       "      <td>POLYGON ((30.83385 3.50917, 29.95350 4.17370, ...</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>177 rows × 6 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                            pop_est      continent iso_a3  gdp_md_est  \\\n",
       "name                                                                    \n",
       "Fiji                         920938        Oceania    FJI      8374.0   \n",
       "Tanzania                   53950935         Africa    TZA    150600.0   \n",
       "W. Sahara                    603253         Africa    ESH       906.5   \n",
       "Canada                     35623680  North America    CAN   1674000.0   \n",
       "United States of America  326625791  North America    USA  18560000.0   \n",
       "...                             ...            ...    ...         ...   \n",
       "Serbia                      7111024         Europe    SRB    101800.0   \n",
       "Montenegro                   642550         Europe    MNE     10610.0   \n",
       "Kosovo                      1895250         Europe    -99     18490.0   \n",
       "Trinidad and Tobago         1218208  North America    TTO     43570.0   \n",
       "S. Sudan                   13026129         Africa    SSD     20880.0   \n",
       "\n",
       "                                                                   geometry  \\\n",
       "name                                                                          \n",
       "Fiji                      MULTIPOLYGON (((180.00000 -16.06713, 180.00000...   \n",
       "Tanzania                  POLYGON ((33.90371 -0.95000, 34.07262 -1.05982...   \n",
       "W. Sahara                 POLYGON ((-8.66559 27.65643, -8.66512 27.58948...   \n",
       "Canada                    MULTIPOLYGON (((-122.84000 49.00000, -122.9742...   \n",
       "United States of America  MULTIPOLYGON (((-122.84000 49.00000, -120.0000...   \n",
       "...                                                                     ...   \n",
       "Serbia                    POLYGON ((18.82982 45.90887, 18.82984 45.90888...   \n",
       "Montenegro                POLYGON ((20.07070 42.58863, 19.80161 42.50009...   \n",
       "Kosovo                    POLYGON ((20.59025 41.85541, 20.52295 42.21787...   \n",
       "Trinidad and Tobago       POLYGON ((-61.68000 10.76000, -61.10500 10.890...   \n",
       "S. Sudan                  POLYGON ((30.83385 3.50917, 29.95350 4.17370, ...   \n",
       "\n",
       "                          characters  \n",
       "name                                  \n",
       "Fiji                             1.0  \n",
       "Tanzania                         1.0  \n",
       "W. Sahara                        0.0  \n",
       "Canada                           4.0  \n",
       "United States of America         7.0  \n",
       "...                              ...  \n",
       "Serbia                           0.0  \n",
       "Montenegro                       0.0  \n",
       "Kosovo                           0.0  \n",
       "Trinidad and Tobago              2.0  \n",
       "S. Sudan                         1.0  \n",
       "\n",
       "[177 rows x 6 columns]"
      ]
     },
     "execution_count": 95,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "merged"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 96,
   "id": "2baba3c3",
   "metadata": {},
   "outputs": [],
   "source": [
    "nA = merged[merged.isna().any(axis=1)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 97,
   "id": "a87dbcf9",
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>pop_est</th>\n",
       "      <th>continent</th>\n",
       "      <th>iso_a3</th>\n",
       "      <th>gdp_md_est</th>\n",
       "      <th>geometry</th>\n",
       "      <th>characters</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>name</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>N. Cyprus</th>\n",
       "      <td>265100</td>\n",
       "      <td>Asia</td>\n",
       "      <td>-99</td>\n",
       "      <td>3600.0</td>\n",
       "      <td>POLYGON ((32.73178 35.14003, 32.80247 35.14550...</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Somaliland</th>\n",
       "      <td>3500000</td>\n",
       "      <td>Africa</td>\n",
       "      <td>-99</td>\n",
       "      <td>12250.0</td>\n",
       "      <td>POLYGON ((48.94820 11.41062, 48.94820 11.41062...</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            pop_est continent iso_a3  gdp_md_est  \\\n",
       "name                                               \n",
       "N. Cyprus    265100      Asia    -99      3600.0   \n",
       "Somaliland  3500000    Africa    -99     12250.0   \n",
       "\n",
       "                                                     geometry  characters  \n",
       "name                                                                       \n",
       "N. Cyprus   POLYGON ((32.73178 35.14003, 32.80247 35.14550...         NaN  \n",
       "Somaliland  POLYGON ((48.94820 11.41062, 48.94820 11.41062...         NaN  "
      ]
     },
     "execution_count": 97,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "nA"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1eee20b6",
   "metadata": {},
   "source": [
    "Both Northern Cyprus and Somaliland are not internationally recognised and thus not included in the CLDR list."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "20ae30a7",
   "metadata": {},
   "source": [
    "# Final plot\n",
    "\n",
    "```cmap``` can be changed to [one of these beautiful colour schemes](https://matplotlib.org/1.2.1/mpl_examples/pylab_examples/show_colormaps.pdf), although I think that ```'PuRd'``` is absolutely magnificient."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 98,
   "id": "04606c32",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1080x504 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "ax2 = merged.plot(figsize=(15,7), edgecolor=u'white', cmap='PuRd',column='characters', legend = True)\n",
    "ax2.axis('scaled')\n",
    "plt.savefig(\"../plots/map_top15.png\", dpi=600)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "8f9ecaab",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python [conda env:geo_env]",
   "language": "python",
   "name": "conda-env-geo_env-py"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.10.4"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}
